AI/ML Engineer in the making. Building at the intersection of machine learning and hardware.
B.Tech Electrical Engineering · NIT Hamirpur · 9.00 CGPA. I build ML systems and IoT hardware with on-device inference — from deployed web apps to embedded devices — working toward research internships in Edge AI / TinyML.
- Built a neural network from first principles in raw NumPy — forward/backward pass, gradient descent, verified on XOR
- Deployed CineMatch, a content-based recommender (TF-IDF + cosine similarity), Dockerized and live on Railway
- Built Fire-Volt Green, an ESP32 + TEG-based IoT vehicle converting crop stubble to electricity — 3rd place, NIMBUS 2026
- Cleared JEE Advanced · 2nd place, Integration Bee @ NIT Hamirpur
Currently deep in deep learning and Gen-AI.
| Project | Description | Stack |
|---|---|---|
| Neural Network from Scratch | Forward prop, backprop & gradient descent from first principles — no PyTorch/TensorFlow — verified on XOR | NumPy · Python |
| Fire-Volt Green | IoT vehicle converting crop stubble to electricity via 12–16 TEG modules — 3rd place, NIMBUS 2026 | ESP32 · TEG · Python |
| CineMatch | Content-based movie recommender, Dockerized full-stack app | TF-IDF · FastAPI · Docker · Railway |
| Laptop Price Predictor | Regression model comparing 4 algorithms · R² = 0.871 | Random Forest · Scikit-learn · Streamlit |
| Olympics Analysis Dashboard | Interactive dashboard across 120 years of Olympic history | Pandas · Plotly · Streamlit |
Full list on my GitHub and portfolio.
